Non-repetitive trajectory tracking for joint position constrained robot manipulators using iterative learning control

Author(s):  
Xu Jin
2018 ◽  
Vol 40 (15) ◽  
pp. 4105-4114 ◽  
Author(s):  
Farah Bouakrif ◽  
Michel Zasadzinski

This paper deals with Iterative Learning Control (ILC) design to solve the trajectory tracking problem for rigid robot manipulators subject to external disturbances, and performing repetitive tasks. A high order ILC scheme is synthetized; this controller contains the information (errors) of several iterations and not only of one iteration. It has been shown that the closed loop system (robot plus controller) is asymptotically stable, over the whole finite time interval, when the iteration number tends to infinity. This proof is based upon the use of a Lyapunov-like positive definite sequence, which is shown to be monotonically decreasing under the proposed controller scheme. Finally, simulation results on two-link manipulator are provided to illustrate the effectiveness of the proposed controller.


Author(s):  
Michele Pierallini ◽  
Franco Angelini ◽  
Riccardo Mengacci ◽  
Alessandro Palleschi ◽  
Antonio Bicchi ◽  
...  

2019 ◽  
Vol 52 (15) ◽  
pp. 358-363
Author(s):  
Yu-Hsiu Lee ◽  
Sheng-Chieh Hsu ◽  
Yan-Yi Du ◽  
Jwu-Sheng Hu ◽  
Tsu-Chin Tsao

Sign in / Sign up

Export Citation Format

Share Document